The hematology laboratory in blood doping (bd): 2014 update on the athlete biological passport (APB)

Introduction: Blood doping (BD) is the use of Erythropoietic Stimulating Agents (ESAs) and/or transfusion to increase aerobic performance in athletes. Direct toxicologic techniques are insufficient to unmask sophisticated doping protocols. The Hematological module of the ABP (World Anti-Doping Agency), associates decision support technology and expert assessment to indirectly detect BD hematological effects. Methods: The ABP module is based on blood parameters, under strict pre-analytical and analytical rules for collection, storage and transport at 2-12°C, internal and external QC. Accuracy, reproducibility and interlaboratory harmonization fulfill forensic standard. Blood samples are collected in competition and out-ofcompetition. Primary parameters for longitudinal monitoring are: - hemoglobin (HGB); - reticulocyte percentage (RET); - OFF score, indicator of suppressed erythropoiesis, calculated as [HGB(g/L) * 60-√RET%]. Statistical calculation predicts individual expected limits by probabilistic inference. Secondary parameters are RBC, HCT, MCHC-MCH-MCV-RDW-IFR. ABP profiles flagged as atypical are review by experts in hematology, pharmacology, sports medicine or physiology, and classified as: - normal - suspect (to target) - likely due to BD - likely due to pathology. Results: Thousands of athletes worldwide are currently monitored. Since 2010, at least 35 athletes have been sanctioned and others are prosecuted on the sole basis of abnormal ABP, with a 240% increase of positivity to direct tests for ESA, thanks to improved targeting of suspicious athletes (WADA data). Specific doping scenarios have been identified by the Experts (Table and Figure). Figure. Typical HGB and RET profiles in two highly suspicious athletes. A. Sample 2: simultaneous increases in HGB and RET (likely ESA stimulation) in a male. B. Samples 3, 6 and 7: "OFF" picture, with high HGB and low RET in a female. Sample 10: normal HGB and increased RET (ESA or blood withdrawal). Conclusions: ABP is a powerful tool for indirect doping detection, based on the recognition of specific, unphysiological changes triggered by blood doping. The effect of factors of heterogeneity, such as sex and altitude, must also be considered. Schumacher YO, et al. Drug Test Anal 2012, 4:846-853. Sottas PE, et al. Clin Chem 2011, 57:969-976.

Recognition judgments and the performance of the recognition heuristic depend on the size of the reference class

In a series of three experiments, participants made inferences about which one of a pair of two objects scored higher on a criterion. The first experiment was designed to contrast the prediction of Probabilistic Mental Model theory (Gigerenzer, Hoffrage, & Kleinbölting, 1991) concerning sampling procedure with the hard-easy effect. The experiment failed to support the theory's prediction that a particular pair of randomly sampled item sets would differ in percentage correct; but the observation that German participants performed practically as well on comparisons between U.S. cities (many of which they did not even recognize) than on comparisons between German cities (about which they knew much more) ultimately led to the formulation of the recognition heuristic. Experiment 2 was a second, this time successful, attempt to unconfound item difficulty and sampling procedure. In Experiment 3, participants' knowledge and recognition of each city was elicited, and how often this could be used to make an inference was manipulated. Choices were consistent with the recognition heuristic in about 80% of the cases when it discriminated and people had no additional knowledge about the recognized city (and in about 90% when they had such knowledge). The frequency with which the heuristic could be used affected the percentage correct, mean confidence, and overconfidence as predicted. The size of the reference class, which was also manipulated, modified these effects in meaningful and theoretically important ways.

Prevalence of nursing diagnosis of fluid volume excess in patients undergoing hemodialysis

Objective: To identify the prevalence of nursing diagnosis of fluid volume excess and their defining characteristics in hemodialysis patients and the association between them. Method: Cross-sectional study conducted in two steps. We interviewed 100 patients between the months of December 2012 and April 2013 in a teaching hospital and one hemodialysis clinic. The inference was performed by diagnostician nurses between July and September 2013. Results: The diagnostic studied was identified in 82% of patients. The characteristics that were statistically associated: bounding pulses, pulmonary congestion, jugular vein distention, edema, change in electrolytes, weight gain, intake greater than output and abnormal breath sounds. Among these, edema and weight gain had the highest chances for the development of this diagnostic. Conclusion: The analyzed diagnostic is prevalent in this population and eight characteristics presented significant association.


Urinary incontinence nursing diagnoses in patients with stroke

Abstract OBJECTIVE Identifying the prevalence of Stress urinary incontinence (SUI), Urge urinary incontinence (UUI), Functional urinary incontinence (FUI), Overflow urinary incontinence (OUI) and Reflex urinary incontinence (RUI) nursing diagnoses and their defining characteristics in stroke patients. METHOD A cross-sectional study with 156 patients treated in a neurological clinic. Data were collected through interviews and forwarded to nurses for diagnostic inference. RESULTS 92.3% of the patients had at least one of the studied diagnoses; OUI showed the highest prevalence (72.4%), followed by FUI (53.2%), RUI (50.0%), UUI (41.0%) and SUI (37.8%). Overdistended bladder and reports of inability to reach the toilet in time to avoid urine loss were the most prevalent defining characteristics. A statistically significant association of the defining characteristics with the studied diagnosis was verified. CONCLUSION The five incontinence diagnoses were identified in the evaluated patients, with different prevalence.

Aitchison Geometry for Probability and Likelihood as a new approach to mathematical statistics

The Aitchison vector space structure for the simplex is generalized to a Hilbert space structure A2(P) for distributions and likelihoods on arbitrary spaces. Centralnotations of statistics, such as Information or Likelihood, can be identified in the algebraical structure of A2(P) and their corresponding notions in compositional data analysis, such as Aitchison distance or centered log ratio transform.In this way very elaborated aspects of mathematical statistics can be understoodeasily in the light of a simple vector space structure and of compositional data analysis. E.g. combination of statistical information such as Bayesian updating,combination of likelihood and robust M-estimation functions are simple additions/perturbations in A2(Pprior). Weighting observations corresponds to a weightedaddition of the corresponding evidence.Likelihood based statistics for general exponential families turns out to have aparticularly easy interpretation in terms of A2(P). Regular exponential families formfinite dimensional linear subspaces of A2(P) and they correspond to finite dimensionalsubspaces formed by their posterior in the dual information space A2(Pprior).The Aitchison norm can identified with mean Fisher information. The closing constant itself is identified with a generalization of the cummulant function and shown to be Kullback Leiblers directed information. Fisher information is the local geometry of the manifold induced by the A2(P) derivative of the Kullback Leibler information and the space A2(P) can therefore be seen as the tangential geometry of statistical inference at the distribution P.The discussion of A2(P) valued random variables, such as estimation functionsor likelihoods, give a further interpretation of Fisher information as the expected squared norm of evidence and a scale free understanding of unbiased reasoning

Compositional Data in Biomedical Research

Modern methods of compositional data analysis are not well known in biomedical research.Moreover, there appear to be few mathematical and statistical researchersworking on compositional biomedical problems. Like the earth and environmental sciences,biomedicine has many problems in which the relevant scienti c information isencoded in the relative abundance of key species or categories. I introduce three problemsin cancer research in which analysis of compositions plays an important role. Theproblems involve 1) the classi cation of serum proteomic pro les for early detection oflung cancer, 2) inference of the relative amounts of di erent tissue types in a diagnostictumor biopsy, and 3) the subcellular localization of the BRCA1 protein, and it'srole in breast cancer patient prognosis. For each of these problems I outline a partialsolution. However, none of these problems is \solved". I attempt to identify areas inwhich additional statistical development is needed with the hope of encouraging morecompositional data analysts to become involved in biomedical research

Stepwise multiple testing as formalized data snooping

It is common in econometric applications that several hypothesis tests arecarried out at the same time. The problem then becomes how to decide whichhypotheses to reject, accounting for the multitude of tests. In this paper,we suggest a stepwise multiple testing procedure which asymptoticallycontrols the familywise error rate at a desired level. Compared to relatedsingle-step methods, our procedure is more powerful in the sense that itoften will reject more false hypotheses. In addition, we advocate the useof studentization when it is feasible. Unlike some stepwise methods, ourmethod implicitly captures the joint dependence structure of the teststatistics, which results in increased ability to detect alternativehypotheses. We prove our method asymptotically controls the familywise errorrate under minimal assumptions. We present our methodology in the context ofcomparing several strategies to a common benchmark and deciding whichstrategies actually beat the benchmark. However, our ideas can easily beextended and/or modied to other contexts, such as making inference for theindividual regression coecients in a multiple regression framework. Somesimulation studies show the improvements of our methods over previous proposals. We also provide an application to a set of real data.

How accurate is the current picture of human genetic variation?

Our understanding of the distribution of worldwide human genomic diversity has greatly increased over recent years thanks to the availability of large data sets derived from short tandem repeats (STRs), insertion deletion polymorphisms (indels) and single nucleotide polymorphisms (SNPs). A concern, however, is that the current picture of worldwide human genomic diversity may be inaccurate because of biases in the selection process of genetic markers (so-called 'ascertainment bias'). To evaluate this problem, we first compared the distribution of genomic diversity between these three types of genetic markers in the populations from the HGDP-CEPH panel for evidence of bias or incongruities. In a second step, using a very relaxed set of criteria to prevent the intrusion of bias, we developed a new set of unbiased STR markers and compared the results against those from available panels. Contrarily to recent claims, our results show that the STR markers suffer from no discernible bias, and can thus be used as a baseline reference for human genetic diversity and population differentiation. The bias on SNPs is moderate compared to that on the set of indels analysed, which we recommend should be avoided for work describing the distribution of human genetic diversity or making inference on human settlement history.

Modeling the forensic two-trace problem with Bayesian networks

The forensic two-trace problem is a perplexing inference problem introduced by Evett (J Forensic Sci Soc 27:375-381, 1987). Different possible ways of wording the competing pair of propositions (i.e., one proposition advanced by the prosecution and one proposition advanced by the defence) led to different quantifications of the value of the evidence (Meester and Sjerps in Biometrics 59:727-732, 2003). Here, we re-examine this scenario with the aim of clarifying the interrelationships that exist between the different solutions, and in this way, produce a global vision of the problem. We propose to investigate the different expressions for evaluating the value of the evidence by using a graphical approach, i.e. Bayesian networks, to model the rationale behind each of the proposed solutions and the assumptions made on the unknown parameters in this problem.

Spanning tests in return and stochastic discount factor mean-variance frontiers: A unifying approach

We propose new spanning tests that assess if the initial and additional assets share theeconomically meaningful cost and mean representing portfolios. We prove their asymptoticequivalence to existing tests under local alternatives. We also show that unlike two-step oriterated procedures, single-step methods such as continuously updated GMM yield numericallyidentical overidentifyng restrictions tests, so there is arguably a single spanning test.To prove these results, we extend optimal GMM inference to deal with singularities in thelong run second moment matrix of the influence functions. Finally, we test for spanningusing size and book-to-market sorted US stock portfolios.

The European Social Survey. Methodological aspects

From a scientific point of view, surveys are undoubtedly a valuable tool for the knowledge of the social and political reality. They are widely used in the social sciences research. However, the researcher's task is often disturbed by a series of deficiencies related to some technical aspects that make difficult both the inference and the comparison. The main aim of the present paper is to report and justify the European Social Survey's technical specifications addressed to avoid and/or minimize such deficiencies. The article also gives a characterization of the non-respondents in Spain obtained from the analysis of the 2002 fieldwork data file.

Seeing the Wood through the Trees: The Current State of Higher Systematics in the Strepsirhini.

Strepsirhines comprise 10 living or recently extinct families, ≥50% of extant primate families. Their phylogenetic relationships have been intensively studied, but common topologies have only recently emerged; e.g. all recent reconstructions link the Lepilemuridae and Cheirogaleidae. The position of the indriids, however, remains uncertain, and molecular studies have placed them as the sister to every clade except Daubentonia, the preferred sister group of morphologists. The node subtending Afro-Asian lorisids has been similarly elusive. We probed these phylogenetic inconsistencies using a test data set including 20 strepsirhine taxa and 2 outgroups represented by 3,543 mtDNA base pairs, and 43 selected morphological characters, subjecting the data to maximum parsimony, maximum likelihood and Bayesian inference analyses, and reconstructing topology and node ages jointly from the molecular data using relaxed molecular clock analyses. Our permutations yielded compatible but not identical evolutionary histories, and currently popular techniques seem unable to deal adequately with morphological data. We investigated the influence of morphological characters on tree topologies, and examined the effect of taxon sampling in two experiments: (1) we removed the molecular data only for 5 endangered Malagasy taxa to simulate 'extinction leaving a fossil record'; (2) we removed both the sequence and morphological data for these taxa. Topologies were affected more by the inclusion of morphological data only, indicating that palaeontological studies that involve inserting a partial morphological data set into a combined data matrix of extant species should be interpreted with caution. The gap of approximately 10 million years between the daubentoniid divergence and those of the other Malagasy families deserves more study. The apparently contemporaneous divergence of African and non-daubentoniid Malagasy families 40-30 million years ago may be related to regional plume-induced uplift followed by a global period of cooling and drying. © 2013 S. Karger AG, Basel.

What comes to mind

We present a model of intuitive inference, called local thinking, in which anagent combines data received from the external world with information retrieved frommemory to evaluate a hypothesis. In this model, selected and limited recall ofinformation follows a version of the respresentativeness heuristic. The model canaccount for some of the evidence on judgment biases, including conjunction anddisjunction fallacies, but also for several anomalies related to demand for insurance.

Experiencing simulated outcomes

Whereas much literature has documented difficulties in making probabilistic inferences, it hasalso emphasized the importance of task characteristics in determining judgmental accuracy.Noting that people exhibit remarkable efficiency in encoding frequency information sequentially,we construct tasks that exploit this ability by requiring people to experience the outcomes ofsequentially simulated data. We report two experiments. The first involved seven well-knownprobabilistic inference tasks. Participants differed in statistical sophistication and answered withand without experience obtained through sequentially simulated outcomes in a design thatpermitted both between- and within-subject analyses. The second experiment involvedinterpreting the outcomes of a regression analysis when making inferences for investmentdecisions. In both experiments, even the statistically naïve make accurate probabilistic inferencesafter experiencing sequentially simulated outcomes and many prefer this presentation format. Weconclude by discussing theoretical and practical implications.

A leverage theory of reputation building with co-branding: Complementarity in reputation building

We present a leverage theory of reputation building with co-branding. We showthat under certain conditions, co-branding that links unknown firms in a new sectorwith established firms in a mature sector allows the unknown firms to signal a highproduct quality and establish their own reputation. We compare this situationwith a benchmark in which both sectors are new and firms signal their qualityonly with prices. We investigate how this comparison is affected by the nature ofthe technology linking the two sectors and a cross-sector inference problem thatconsumers might face in identifying the true cause of product failure. We find thatco-branding facilitates the process in which a Þrm in the new sector to signal itsproduct quality only if the co-branding sectors produce complementary inputs andconsumers face a cross-sector inference problem. We apply our insight to economicsof superstars, multinational firms and co-authorship.